Papers Object Segmentation
“Object Segmentation” 태그가 달린 논문 86편 · 필터 해제
Computer Vision-Based Early Detection of Container Loss at Sea
Containerised shipping underpins global trade, yet container loss at sea remains a persistent safety, environmental, and economic challenge. Despite compliance with Cargo Securing Manuals, dynamic maritime conditions suc…
Object SegmentationObject TrackingGenMatter: Perceiving Physical Objects with Generative Matter Models
Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly detect and segment moving entities that constitute independently moveable …
Object SegmentationScene UnderstandingEfficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation
Reliable object perception is necessary for general-purpose service robots. Open-vocabulary detectors struggle to generalize beyond a few classes and fully supervised training of object detectors requires time-intensive …
Object SegmentationUnsupervised Learning of Inter-Object Relationships via Group Homomorphism
While current deep learning models achieve high performance by learning statistical correlations from vast datasets,which stands in stark contrast to human learning. They lack the flexibility of humans-particularly preve…
Representation LearningObject SegmentationNG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation
Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accurately in 3DGS remains challenging due to the discrete nature of Gaus…
Novel View SynthesisObject SegmentationVGGT-Segmentor: Geometry-Enhanced Cross-View Segmentation
Instance-level object segmentation across disparate egocentric and exocentric views is a fundamental challenge in visual understanding, critical for applications in embodied AI and remote collaboration. This task is exce…
Semantic SegmentationObject SegmentationPASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation
Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recycling and weeding. Existing perception systems frequently fail to sa…
Object SegmentationIdentity-Aware U-Net: Fine-grained Cell Segmentation via Identity-Aware Representation Learning
Precise segmentation of objects with highly similar shapes remains a challenging problem in dense prediction, especially in scenarios with ambiguous boundaries, overlapping instances, and weak inter-instance visual diffe…
Representation LearningObject SegmentationCell SegmentationMetric LearningGeneralizable task-oriented object grasping through LLM-guided ontology and similarity-based planning
Task-oriented grasping (TOG) is more challenging than simple object grasping because it requires precise identification of object parts and careful selection of grasping areas to ensure effective and robust manipulation.…
Object SegmentationPoint CloudsUnified Spatio-Temporal Token Scoring for Efficient Video VLMs
Token pruning is essential for enhancing the computational efficiency of vision-language models (VLMs), particularly for video-based tasks where temporal redundancy is prevalent. Prior approaches typically prune tokens e…
Computational EfficiencyObject SegmentationAction RecognitionFEEL (Force-Enhanced Egocentric Learning): A Dataset for Physical Action Understanding
We introduce FEEL (Force-Enhanced Egocentric Learning), the first large-scale dataset pairing force measurements gathered from custom piezoresistive gloves with egocentric video. Our gloves enable scalable data collectio…
Representation LearningAction UnderstandingObject SegmentationHuman-like Object Grouping in Self-supervised Vision Transformers
Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object segmentation properties. However, their alignment with human object perception …
Object SegmentationA novel Framework for Open-Vocabulary Multi-Object Recognition using CLIP
To address the limitations of existing open-vocabulary object recognition methods, including high system complexity, substantial training costs, and limited generalization capability, this paper proposes a novel Open-Voc…
Object SegmentationObject RecognitionAn Extended Topological Model For High-Contrast Optical Flow
In this paper, we identify low-dimensional models for dense core subsets in the space of $3\times 3$ high-contrast optical flow patches sampled from the Sintel dataset. In particular, we leverage the theory of approximat…
Object SegmentationGarmentPile++: Affordance-Driven Cluttered Garments Retrieval with Vision-Language Reasoning
Garment manipulation has attracted increasing attention due to its critical role in home-assistant robotics. However, the majority of existing garment manipulation works assume an initial state consisting of only one gar…
Object SegmentationInstruction-based Image Editing with Planning, Reasoning, and Generation
Editing images via instruction provides a natural way to generate interactive content, but it is a big challenge due to the higher requirement of scene understanding and generation. Prior work utilizes a chain of large l…
Object SegmentationScene UnderstandingImage EditingSPOT: Spatio-Temporal Obstacle-free Trajectory Planning for UAVs in Unknown Dynamic Environments
We address the problem of reactive motion planning for quadrotors operating in unknown environments with dynamic obstacles. Our approach leverages a 4-dimensional spatio-temporal planner, integrated with vision-based Saf…
Collision AvoidanceObject SegmentationTrajectory PlanningMotion PlanningSmall but Mighty: Dynamic Wavelet Expert-Guided Fine-Tuning of Large-Scale Models for Optical Remote Sensing Object Segmentation
Accurately localizing and segmenting relevant objects from optical remote sensing images (ORSIs) is critical for advancing remote sensing applications. Existing methods are typically built upon moderate-scale pre-trained…
Object SegmentationMOSAIC-GS: Monocular Scene Reconstruction via Advanced Initialization for Complex Dynamic Environments
We present MOSAIC-GS, a novel, fully explicit, and computationally efficient approach for high-fidelity dynamic scene reconstruction from monocular videos using Gaussian Splatting. Monocular reconstruction is inherently …
Object SegmentationPoint TrackingPartImageNet++ Dataset: Enhancing Visual Models with High-Quality Part Annotations
To address the scarcity of high-quality part annotations in existing datasets, we introduce PartImageNet++ (PIN++), a dataset that provides detailed part annotations for all categories in ImageNet-1K. With 100 annotated …
Object SegmentationObject RecognitionFew-Shot Learning